Search Results for author: Gang Wang

Found 151 papers, 27 papers with code

Flexible Job Shop Scheduling via Dual Attention Network Based Reinforcement Learning

1 code implementation9 May 2023 Runqing Wang, Gang Wang, Jian Sun, Fang Deng, Jie Chen

The complex relationships between operations and machines are represented precisely and concisely, for which a dual-attention network (DAN) comprising several interconnected operation message attention blocks and machine message attention blocks is proposed.

Decision Making Job Shop Scheduling +2

Learning Robust Data-based LQG Controllers from Noisy Data

no code implementations2 May 2023 Wenjie Liu, Jian Sun, Gang Wang, Francesco Bullo, Jie Chen

In this work, a data-based formulation for computing the steady-state Kalman gain is proposed based on semi-definite programming (SDP) using some noise-free input-state-output data.

FedGH: Heterogeneous Federated Learning with Generalized Global Header

no code implementations23 Mar 2023 Liping Yi, Gang Wang, Xiaoguang Liu, Zhuan Shi, Han Yu

It is a communication and computation-efficient model-heterogeneous FL framework which trains a shared generalized global prediction header with representations extracted by heterogeneous extractors for clients' models at the FL server.

Federated Learning Privacy Preserving

P-MMF: Provider Max-min Fairness Re-ranking in Recommender System

1 code implementation12 Mar 2023 Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang, Zhenghua Dong

In this paper, we proposed an online re-ranking model named Provider Max-min Fairness Re-ranking (P-MMF) to tackle the problem.

Fairness Recommendation Systems +1

Robust consensus control of second-order uncertain multiagent systems with velocity and input constraints (extended version)

no code implementations1 Mar 2023 Gang Wang, Zongyu Zuo, Chaoli Wang

In this paper, we investigate the consensus problem of second-order multiagent systems under directed graphs.

EdgeYOLO: An Edge-Real-Time Object Detector

1 code implementation15 Feb 2023 Shihan Liu, Junlin Zha, Jian Sun, Zhuo Li, Gang Wang

This paper proposes an efficient, low-complexity and anchor-free object detector based on the state-of-the-art YOLO framework, which can be implemented in real time on edge computing platforms.

Data Augmentation Edge-computing

Self-triggered Resilient Stabilization of Linear Systems with Quantized Output

no code implementations14 Feb 2023 Wenjie Liu, Masashi Wakaiki, Jian Sun, Gang Wang, Jie Chen

If, in addition, the transmission protocols at the controller-to-actuator (C-A) and sensor-to-controller (S-C) channels can be adapted, the self-triggered control architecture can be considerably simplified, leveraging a delicate observer-based deadbeat controller to eliminate the need for running the controller in parallel at the encoder side.

Minimum Error Entropy Rauch-Tung-Striebel Smoother

no code implementations14 Jan 2023 Jiacheng He, Hongwei Wang, Gang Wang, Shan Zhong, Bei Peng

Outliers and impulsive disturbances often cause heavy-tailed distributions in practical applications, and these will degrade the performance of Gaussian approximation smoothing algorithms.

State Estimation of Wireless Sensor Networks in the Presence of Data Packet Drops and Non-Gaussian Noise

no code implementations14 Jan 2023 Jiacheng He, Gang Wang, Xuemei Mao, Song Gao, Bei Peng

Distributed Kalman filter approaches based on the maximum correntropy criterion have recently demonstrated superior state estimation performance to that of conventional distributed Kalman filters for wireless sensor networks in the presence of non-Gaussian impulsive noise.

Robust Ellipse Fitting Based on Maximum Correntropy Criterion With Variable Center

no code implementations24 Oct 2022 Wei Wang, Gang Wang, Chenlong Hu, K. C. Ho

For single ellipse fitting, we formulate a non-convex optimization problem to estimate the kernel bandwidth and center and divide it into two subproblems, each estimating one parameter.

Multi-scale Attention Network for Single Image Super-Resolution

1 code implementation28 Sep 2022 Yan Wang, Yusen Li, Gang Wang, Xiaoguang Liu

In this paper, we propose a CNN-based multi-scale attention network (MAN), which consists of multi-scale large kernel attention (MLKA) and a gated spatial attention unit (GSAU), to improve the performance of convolutional SR networks.

Image Super-Resolution Long-range modeling

Learning from Students: Online Contrastive Distillation Network for General Continual Learning

1 code implementation Conference 2022 Jin Li, Zhong Ji, Gang Wang, Qiang Wang, Feng Gao

The goal of General Continual Learning (GCL) is to preserve learned knowledge and learn new knowledge with constant memory from an infinite data stream where task boundaries are blurry.

Continual Learning

Deep learning-based Crop Row Following for Infield Navigation of Agri-Robots

1 code implementation9 Sep 2022 Rajitha de Silva, Grzegorz Cielniak, Gang Wang, Junfeng Gao

A dataset of sugar beet images was created with 43 combinations of 11 field variations found in arable fields.

Autonomous Navigation

Data-Driven Control of Distributed Event-Triggered Network Systems

no code implementations22 Aug 2022 Xin Wang, Jian Sun, Gang Wang, Frank Allgöwer, Jie Chen

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems (a. k. a.

Event-triggered Consensus Control of Heterogeneous Multi-agent Systems: Model- and Data-based Analysis

no code implementations1 Aug 2022 Xin Wang, Jian Sun, Gang Wang, Jie Chen

This article deals with model- and data-based consensus control of heterogenous leader-following multi-agent systems (MASs) under an event-triggering transmission scheme.

Data-driven Self-triggered Control via Trajectory Prediction

no code implementations18 Jul 2022 Wenjie Liu, Jian Sun, Gang Wang, Francesco Bullo, Jie Chen

Self-triggered control, a well-documented technique for reducing the communication overhead while ensuring desired system performance, is gaining increasing popularity.

Trajectory Prediction

Mixed-Phoneme BERT: Improving BERT with Mixed Phoneme and Sup-Phoneme Representations for Text to Speech

no code implementations31 Mar 2022 Guangyan Zhang, Kaitao Song, Xu Tan, Daxin Tan, Yuzi Yan, Yanqing Liu, Gang Wang, Wei Zhou, Tao Qin, Tan Lee, Sheng Zhao

However, the works apply pre-training with character-based units to enhance the TTS phoneme encoder, which is inconsistent with the TTS fine-tuning that takes phonemes as input.

Boosting Black-Box Adversarial Attacks with Meta Learning

no code implementations28 Mar 2022 Junjie Fu, Jian Sun, Gang Wang

Extensive experiments demonstrate that our method can not only improve the attack success rates, but also reduces the number of queries compared to other methods.

Adversarial Attack Meta-Learning

A Spatial-Temporal Attention Multi-Graph Convolution Network for Ride-Hailing Demand Prediction Based on Periodicity with Offset

no code implementations23 Mar 2022 Dong Xing, Chenguang Zhao, Gang Wang

To improve the efficiency of ride-hailing service, accurate prediction of transportation demand is a fundamental challenge.

Model-Based and Data-Driven Control of Event- and Self-Triggered Discrete-Time LTI Systems

no code implementations16 Feb 2022 Xin Wang, Julian Berberich, Jian Sun, Gang Wang, Frank Allgöwer, Jie Chen

To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived.


Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers

no code implementations11 Feb 2022 Limin Yang, Zhi Chen, Jacopo Cortellazzi, Feargus Pendlebury, Kevin Tu, Fabio Pierazzi, Lorenzo Cavallaro, Gang Wang

Empirically, we show that existing backdoor attacks in malware classifiers are still detectable by recent defenses such as MNTD.

Backdoor Attack

Online State Estimation for Supervisor Synthesis in Discrete-Event Systems with Communication Delays and Losses

no code implementations13 Jan 2022 Yunfeng Hou, Yunfeng Ji, Gang Wang, Ching-Yen Weng, Qingdu Li

Under the introduced framework, we address the state estimation problem for supervisor synthesis of networked DESs with both communication delays and losses.

Collaborative Uncertainty in Multi-Agent Trajectory Forecasting

no code implementations NeurIPS 2021 Bohan Tang, Yiqi Zhong, Ulrich Neumann, Gang Wang, Ya zhang, Siheng Chen

2) The results of trajectory forecasting benchmarks demonstrate that the CU-based framework steadily helps SOTA systems improve their performances.

Trajectory Forecasting

Data-Driven Resilient Predictive Control under Denial-of-Service

no code implementations25 Oct 2021 Wenjie Liu, Jian Sun, Gang Wang, Francesco Bullo, Jie Chen

Finally, a numerical example is given to validate the effectiveness of the proposed control method.

Data-driven Control of Dynamic Event-triggered Systems with Delays

no code implementations25 Oct 2021 Xin Wang, Jian Sun, Julian Berberich, Gang Wang, Frank Allgöwer, Jie Chen

Data-based representations for time-invariant linear systems with known or unknown system input matrices are first developed, along with a novel class of dynamic triggering schemes for sampled-data systems with time delays.

DelightfulTTS: The Microsoft Speech Synthesis System for Blizzard Challenge 2021

1 code implementation25 Oct 2021 Yanqing Liu, Zhihang Xu, Gang Wang, Kuan Chen, Bohan Li, Xu Tan, Jinzhu Li, Lei He, Sheng Zhao

The goal of this challenge is to synthesize natural and high-quality speech from text, and we approach this goal in two perspectives: The first is to directly model and generate waveform in 48 kHz sampling rate, which brings higher perception quality than previous systems with 16 kHz or 24 kHz sampling rate; The second is to model the variation information in speech through a systematic design, which improves the prosody and naturalness.

Speech Synthesis

Balancing Value Underestimation and Overestimation with Realistic Actor-Critic

1 code implementation19 Oct 2021 Sicen Li, Qinyun Tang, Yiming Pang, Xinmeng Ma, Gang Wang

Model-free deep reinforcement learning (RL) has been successfully applied to challenging continuous control domains.

Continuous Control Efficient Exploration +2

A New Approach for Verification of Delay Coobservability of Discrete-Event Systems

no code implementations1 Oct 2021 Yunfeng Hou, Qingdu Li, Yunfeng Ji, Gang Wang, Ching-Yen Weng

Thus, techniques for the verification of delay coobservability can be leveraged to verify delay $K$-codiagnosability.

Learning Dual Dynamic Representations on Time-Sliced User-Item Interaction Graphs for Sequential Recommendation

1 code implementation24 Sep 2021 Zeyuan Chen, Wei zhang, Junchi Yan, Gang Wang, Jianyong Wang

Sequential Recommendation aims to recommend items that a target user will interact with in the near future based on the historically interacted items.

Representation Learning Sequential Recommendation

Generalized Minimum Error Entropy for Adaptive Filtering

no code implementations8 Sep 2021 Jiacheng He, Gang Wang, Bei Peng, Zhenyu Feng, Kun Zhang

In our study, a novel concept, called generalized error entropy, utilizing the generalized Gaussian density (GGD) function as the kernel function is proposed.

The 2nd Anti-UAV Workshop & Challenge: Methods and Results

no code implementations23 Aug 2021 Jian Zhao, Gang Wang, Jianan Li, Lei Jin, Nana Fan, Min Wang, Xiaojuan Wang, Ting Yong, Yafeng Deng, Yandong Guo, Shiming Ge, Guodong Guo

The 2nd Anti-UAV Workshop \& Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking.

Object Tracking

Modeling Relevance Ranking under the Pre-training and Fine-tuning Paradigm

no code implementations12 Aug 2021 Lin Bo, Liang Pang, Gang Wang, Jun Xu, Xiuqiang He, Ji-Rong Wen

Experimental results base on three publicly available benchmarks showed that in both of the implementations, Pre-Rank can respectively outperform the underlying ranking models and achieved state-of-the-art performances.

Document Ranking Information Retrieval +3

Resonant Beam Communications with Echo Interference Elimination

no code implementations25 Jun 2021 Mingliang Xiong, Qingwen Liu, Gang Wang, Georgios B. Giannakis, Sihai Zhang, Jinkang Zhu, Chuan Huang

Resonant beam communications (RBCom) is capable of providing wide bandwidth when using light as the carrier.

A Logical Neural Network Structure With More Direct Mapping From Logical Relations

no code implementations22 Jun 2021 Gang Wang

Therefore, in order to represent logical relations more clearly by the neural network structure and to read out logical relations from it, this paper proposes a novel logical ANN model by designing the new logical neurons and links in demand of logical representation.

Medical Diagnosis

Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol

no code implementations22 Mar 2021 Wenjie Liu, Jian Sun, Gang Wang, Francesco Bullo, Jie Chen

When both input and output channels are subject to DoS attacks and quantization, the proposed structure is shown able to decouple the encoding schemes for input, output, and estimated output signals.


A posteriori error analysis of hybrid high-order method for the Stokes problem

no code implementations11 Mar 2021 Yongchao Zhang, Liquan Mei, Gang Wang

We present a residual-based a posteriori error estimator for the hybrid high-order (HHO) method for the Stokes model problem.

Numerical Analysis Numerical Analysis

SceneRec: Scene-Based Graph Neural Networks for Recommender Systems

no code implementations12 Feb 2021 Gang Wang, Ziyi Guo, Xiang Li, Dawei Yin, Shuai Ma

Collaborative filtering has been largely used to advance modern recommender systems to predict user preference.

Collaborative Filtering Recommendation Systems +1

Theory of Plasma-Cascade Instability

no code implementations11 Jan 2021 Vladimir N. Litvinenko, Gang Wang

In this paper we present theory of novel micro-bunching instability.

Plasma Physics Accelerator Physics

Exciton-phonon coupling strength in single-layer MoSe2 at room temperature

no code implementations21 Dec 2020 Donghai Li, Chiara Trovatello, Stefano Dal Conte, Matthias Nuß, Giancarlo Soavi, Gang Wang, Andrea C. Ferrari, Giulio Cerullo, Tobias Brixner

Single-layer transition metal dichalcogenides are at the center of an ever increasing research effort both in terms of fundamental physics and applications.

Mesoscale and Nanoscale Physics Materials Science

Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis

no code implementations NeurIPS 2020 Gang Wang, Songtao Lu, Georgios Giannakis, Gerald Tesauro, Jian Sun

The present contribution deals with decentralized policy evaluation in multi-agent Markov decision processes using temporal-difference (TD) methods with linear function approximation for scalability.

Developing Univariate Neurodegeneration Biomarkers with Low-Rank and Sparse Subspace Decomposition

no code implementations26 Oct 2020 Gang Wang, Qunxi Dong, Jianfeng Wu, Yi Su, Kewei Chen, Qingtang Su, Xiaofeng Zhang, Jinguang Hao, Tao Yao, Li Liu, Caiming Zhang, Richard J Caselli, Eric M Reiman, Yalin Wang

With hippocampal UMIs, the estimated minimum sample sizes needed to detect a 25$\%$ reduction in the mean annual change with 80$\%$ power and two-tailed $P=0. 05$ are 116, 279 and 387 for the longitudinal $A\beta+$ AD, $A\beta+$ mild cognitive impairment (MCI) and $A\beta+$ CU groups, respectively.

SparTerm: Learning Term-based Sparse Representation for Fast Text Retrieval

no code implementations2 Oct 2020 Yang Bai, Xiaoguang Li, Gang Wang, Chaoliang Zhang, Lifeng Shang, Jun Xu, Zhaowei Wang, Fangshan Wang, Qun Liu

Term-based sparse representations dominate the first-stage text retrieval in industrial applications, due to its advantage in efficiency, interpretability, and exact term matching.

Language Modelling Retrieval +1

PDLight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Pressure and Dynamic Light Duration

1 code implementation29 Sep 2020 Chenguang Zhao, Xiaorong Hu, Gang Wang

Existing ineffective and inflexible traffic light control at urban intersections can often lead to congestion in traffic flows and cause numerous problems, such as long delay and waste of energy.


A Traffic Light Dynamic Control Algorithm with Deep Reinforcement Learning Based on GNN Prediction

1 code implementation29 Sep 2020 Xiaorong Hu, Chenguang Zhao, Gang Wang

Then, the results of traffic flow prediction are used in traffic light control, and the agent combines the predicted results with the observed current traffic conditions to dynamically control the phase and duration of the traffic lights at the intersection.

Reinforcement Learning (RL)

Urban Sensing based on Mobile Phone Data: Approaches, Applications and Challenges

no code implementations29 Aug 2020 Mohammadhossein Ghahramani, Mengchu Zhou, Gang Wang

We classify these existing methods and present a taxonomy of the related work by discussing their pros and cons.

Decision Making Marketing

Reinforcement Learning for Caching with Space-Time Popularity Dynamics

no code implementations19 May 2020 Alireza Sadeghi, Georgios B. Giannakis, Gang Wang, Fatemeh Sheikholeslami

With the tremendous growth of data traffic over wired and wireless networks along with the increasing number of rich-media applications, caching is envisioned to play a critical role in next-generation networks.

reinforcement-learning Reinforcement Learning (RL)

Resonant Beam Communications: Principles and Designs

no code implementations18 Apr 2020 Mingliang Xiong, Qingwen Liu, Gang Wang, Georgios B. Giannakis, Chuan Huang

Wireless optical communications (WOC) has carriers up to several hundred terahertz, which offers several advantages, such as ultrawide bandwidth and no electromagnetic interference.

DA4AD: End-to-End Deep Attention-based Visual Localization for Autonomous Driving

no code implementations ECCV 2020 Yao Zhou, Guowei Wan, Shenhua Hou, Li Yu, Gang Wang, Xiaofei Rui, Shiyu Song

We present a visual localization framework based on novel deep attention aware features for autonomous driving that achieves centimeter level localization accuracy.

Autonomous Driving Deep Attention +1

Gauss-Newton Unrolled Neural Networks and Data-driven Priors for Regularized PSSE with Robustness

no code implementations3 Mar 2020 Qiuling Yang, Alireza Sadeghi, Gang Wang, Georgios B. Giannakis, Jian Sun

Numerical tests using real load data on the IEEE $118$-bus benchmark system showcase the improved estimation and robustness performance of the proposed scheme compared with several state-of-the-art alternatives.

Image Denoising Rolling Shutter Correction

Numerical simulation of sky localization for LISA-TAIJI joint observation

no code implementations28 Feb 2020 Gang Wang, Wei-Tou Ni, Wen-Biao Han, Shu-Cheng Yang, Xing-Yu Zhong

The precision of sky localization could be improved by around 1 to 3 times comparing to single LISA at a given percentage of sources.

General Relativity and Quantum Cosmology Astrophysics of Galaxies Instrumentation and Methods for Astrophysics

Scene Text Recognition With Finer Grid Rectification

no code implementations26 Jan 2020 Gang Wang

Scene Text Recognition is a challenging problem because of irregular styles and various distortions.

Scene Text Recognition

Finite-Sample Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation

no code implementations3 Nov 2019 Jun Sun, Gang Wang, Georgios B. Giannakis, Qinmin Yang, Zaiyue Yang

Motivated by the emerging use of multi-agent reinforcement learning (MARL) in engineering applications such as networked robotics, swarming drones, and sensor networks, we investigate the policy evaluation problem in a fully decentralized setting, using temporal-difference (TD) learning with linear function approximation to handle large state spaces in practice.

Multi-agent Reinforcement Learning

Easy First Relation Extraction with Information Redundancy

no code implementations IJCNLP 2019 Shuai Ma, Gang Wang, Yansong Feng, Jinpeng Huai

Many existing relation extraction (RE) models make decisions globally using integer linear programming (ILP).

Relation Extraction

A Statistical Learning Approach to Reactive Power Control in Distribution Systems

no code implementations25 Oct 2019 Qiuling Yang, Alireza Sadeghi, Gang Wang, Georgios B. Giannakis, Jian Sun

Taking a statistical learning viewpoint, the input-output relationship between each grid state and the corresponding optimal reactive power control is parameterized in the present work by a deep neural network, whose unknown weights are learned offline by minimizing the power loss over a number of historical and simulated training pairs.

A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation

no code implementations10 Sep 2019 Gang Wang, Bingcong Li, Georgios B. Giannakis

Motivated by the widespread use of temporal-difference (TD-) and Q-learning algorithms in reinforcement learning, this paper studies a class of biased stochastic approximation (SA) procedures under a mild "ergodic-like" assumption on the underlying stochastic noise sequence.


Semantic Correlation Promoted Shape-Variant Context for Segmentation

1 code implementation CVPR 2019 Henghui Ding, Xudong Jiang, Bing Shuai, Ai Qun Liu, Gang Wang

In this way, the proposed network aggregates the context information of a pixel from its semantic-correlated region instead of a predefined fixed region.

Denoising Semantic Segmentation

Boundary-Aware Feature Propagation for Scene Segmentation

1 code implementation ICCV 2019 Henghui Ding, Xudong Jiang, Ai Qun Liu, Nadia Magnenat Thalmann, Gang Wang

Furthermore, we propose a boundary-aware feature propagation (BFP) module to harvest and propagate the local features within their regions isolated by the learned boundaries in the UAG-structured image.

Scene Segmentation

NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding

3 code implementations12 May 2019 Jun Liu, Amir Shahroudy, Mauricio Perez, Gang Wang, Ling-Yu Duan, Alex C. Kot

Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition.

Action Recognition One-Shot 3D Action Recognition +1

Toward Achieving Robust Low-Level and High-Level Scene Parsing

1 code implementation journal 2019 Bing Shuai, Henghui Ding, Ting Liu, Gang Wang, Xudong Jiang

Furthermore, we introduce a “dense skip” architecture to retain a rich set of low-level information from the pre-trained CNN, which is essential to improve the low-level parsing performance.

Scene Parsing Scene Segmentation +1

2D LiDAR Map Prediction via Estimating Motion Flow with GRU

no code implementations19 Feb 2019 Yafei Song, Yonghong Tian, Gang Wang, Mingyang Li

To tackle this problem, we resort to the motion flow between adjacent maps, as motion flow is a powerful tool to process and analyze the dynamic data, which is named optical flow in video processing.

Optical Flow Estimation Representation Learning

Skeleton-Based Online Action Prediction Using Scale Selection Network

no code implementations8 Feb 2019 Jun Liu, Amir Shahroudy, Gang Wang, Ling-Yu Duan, Alex C. Kot

Since there are significant temporal scale variations in the observed part of the ongoing action at different time steps, a novel window scale selection method is proposed to make our network focus on the performed part of the ongoing action and try to suppress the possible incoming interference from the previous actions at each step.

Skeleton Based Action Recognition

Feature Boosting Network For 3D Pose Estimation

no code implementations15 Jan 2019 Jun Liu, Henghui Ding, Amir Shahroudy, Ling-Yu Duan, Xudong Jiang, Gang Wang, Alex C. Kot

Learning a set of features that are reliable and discriminatively representative of the pose of a hand (or body) part is difficult due to the ambiguities, texture and illumination variation, and self-occlusion in the real application of 3D pose estimation.

3D Hand Pose Estimation 3D Pose Estimation

Real-time Power System State Estimation and Forecasting via Deep Neural Networks

3 code implementations15 Nov 2018 Liang Zhang, Gang Wang, Georgios B. Giannakis

To bypass these hurdles, this paper advocates deep neural networks (DNNs) for real-time power system monitoring.

Rolling Shutter Correction Time Series Analysis

Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks

no code implementations13 Nov 2018 Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu

In this paper, we propose an improved variant of RNN, Multi-Channel RNN (MC-RNN), to dynamically capture and leverage local semantic structure information.

Abstractive Text Summarization Language Modelling +1

Context-Aware Deep Spatio-Temporal Network for Hand Pose Estimation from Depth Images

no code implementations6 Oct 2018 Yiming Wu, Wei Ji, Xi Li, Gang Wang, Jianwei Yin, Fei Wu

As a fundamental and challenging problem in computer vision, hand pose estimation aims to estimate the hand joint locations from depth images.

Hand Pose Estimation

Graininess-Aware Deep Feature Learning for Pedestrian Detection

no code implementations ECCV 2018 Chunze Lin, Jiwen Lu, Gang Wang, Jie zhou

In this paper, we propose a graininess-aware deep feature learning method for pedestrian detection.

Pedestrian Detection

Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization

no code implementations14 Aug 2018 Gang Wang, Georgios B. Giannakis, Jie Chen

In this context, the problem of learning a two-layer ReLU network is approached in a binary classification setting, where the data are linearly separable and a hinge loss criterion is adopted.

Binary Classification

Early action prediction by soft regression

no code implementations IEEE Transactions on Pattern Analysis and Machine Intelligence 2018 Jian-Fang Hu, Wei-Shi Zheng, Lianyang Ma, Gang Wang, Jian-Huang Lai, Jian-Guo Zhang

Our formulation of soft regression framework 1) overcomes a usual assumption in existing early action prediction systems that the progress level of on-going sequence is given in the testing stage; and 2) presents a theoretical framework to better resolve the ambiguity and uncertainty of subsequences at early performing stage.

Early Action Prediction regression +1

Motion-Guided Cascaded Refinement Network for Video Object Segmentation

no code implementations CVPR 2018 Ping Hu, Gang Wang, Xiangfei Kong, Jason Kuen, Yap-Peng Tan

Then, the proposed Cascaded Refinement Network(CRN) takes the coarse segmentation as guidance to generate an accurate segmentation of full resolution.

Optical Flow Estimation Semantic Segmentation +2

Context Contrasted Feature and Gated Multi-Scale Aggregation for Scene Segmentation

1 code implementation CVPR 2018 Henghui Ding, Xudong Jiang, Bing Shuai, Ai Qun Liu, Gang Wang

In this paper, we first propose a novel context contrasted local feature that not only leverages the informative context but also spotlights the local information in contrast to the context.

Scene Segmentation

SSNet: Scale Selection Network for Online 3D Action Prediction

no code implementations CVPR 2018 Jun Liu, Amir Shahroudy, Gang Wang, Ling-Yu Duan, Alex C. Kot

As there are significant temporal scale variations of the observed part of the ongoing action at different progress levels, we propose a novel window scale selection scheme to make our network focus on the performed part of the ongoing action and try to suppress the noise from the previous actions at each time step.

Action Recognition Temporal Action Localization

Nonlinear Dimensionality Reduction for Discriminative Analytics of Multiple Datasets

no code implementations15 May 2018 Jia Chen, Gang Wang, Georgios B. Giannakis

Under certain conditions, dPCA is proved to be least-squares optimal in recovering the component vector unique to the target data relative to background data.

Dimensionality Reduction

Canonical Correlation Analysis of Datasets with a Common Source Graph

no code implementations27 Mar 2018 Jia Chen, Gang Wang, Yanning Shen, Georgios B. Giannakis

Canonical correlation analysis (CCA) is a powerful technique for discovering whether or not hidden sources are commonly present in two (or more) datasets.

Dimensionality Reduction feature selection +2

Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification

no code implementations CVPR 2018 Jianlou Si, Honggang Zhang, Chun-Guang Li, Jason Kuen, Xiangfei Kong, Alex C. Kot, Gang Wang

Typical person re-identification (ReID) methods usually describe each pedestrian with a single feature vector and match them in a task-specific metric space.

Person Re-Identification

Unpaired Image Captioning by Language Pivoting

no code implementations ECCV 2018 Jiuxiang Gu, Shafiq Joty, Jianfei Cai, Gang Wang

Image captioning is a multimodal task involving computer vision and natural language processing, where the goal is to learn a mapping from the image to its natural language description.

Image Captioning

Learning Hierarchical Features for Visual Object Tracking with Recursive Neural Networks

no code implementations6 Jan 2018 Li Wang, Ting Liu, Bing Wang, Xulei Yang, Gang Wang

First, we learn RNN parameters to discriminate between the target object and background in the first frame of a test sequence.

Visual Object Tracking

Solving Most Systems of Random Quadratic Equations

no code implementations NeurIPS 2017 Gang Wang, Georgios Giannakis, Yousef Saad, Jie Chen

For certain random measurement models, the proposed procedure returns the true solution $\bm{x}$ with high probability in time proportional to reading the data $\{(\bm{a}_i;y_i)\}_{1\le i \le m}$, provided that the number $m$ of equations is some constant $c>0$ times the number $n$ of unknowns, that is, $m\ge cn$.

DPCA: Dimensionality Reduction for Discriminative Analytics of Multiple Large-Scale Datasets

no code implementations25 Oct 2017 Gang Wang, Jia Chen, Georgios B. Giannakis

Principal component analysis (PCA) has well-documented merits for data extraction and dimensionality reduction.

Dimensionality Reduction

Stack-Captioning: Coarse-to-Fine Learning for Image Captioning

1 code implementation11 Sep 2017 Jiuxiang Gu, Jianfei Cai, Gang Wang, Tsuhan Chen

On the other hand, multi-stage image caption model is hard to train due to the vanishing gradient problem.

Image Captioning

A Novel Neural Network Model Specified for Representing Logical Relations

no code implementations2 Aug 2017 Gang Wang

Inhibitory links inhibit the connected exciting links conditionally to make this neural network model represent logical relations correctly.

Numerical simulation of time delay interferometry for new LISA, TAIJI and other LISA-like missions

no code implementations28 Jul 2017 Gang Wang, Wei-Tou Ni

In this paper, we follow the same procedure to simulate the time delay interferometry numerically for the new LISA mission and the TAIJI mission together with LISA-like missions of arm length 1, 2, 4, 5 and 6 Gm.

Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology

Beyond Forward Shortcuts: Fully Convolutional Master-Slave Networks (MSNets) with Backward Skip Connections for Semantic Segmentation

no code implementations18 Jul 2017 Abrar H. Abdulnabi, Stefan Winkler, Gang Wang

However, during inference the lower layers do not know about high layer features, although they contain contextual high semantics that benefit low layers to adaptively extract informative features for later layers.

Scene Parsing Semantic Segmentation

Deep Level Sets for Salient Object Detection

no code implementations CVPR 2017 Ping Hu, Bing Shuai, Jun Liu, Gang Wang

Our method drives the network to learn a Level Set function for salient objects so it can output more accurate boundaries and compact saliency.

object-detection RGB Salient Object Detection +2

Global Context-Aware Attention LSTM Networks for 3D Action Recognition

no code implementations CVPR 2017 Jun Liu, Gang Wang, Ping Hu, Ling-Yu Duan, Alex C. Kot

Hence we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for 3D action recognition, which is able to selectively focus on the informative joints in the action sequence with the assistance of global contextual information.

Action Analysis One-Shot 3D Action Recognition +1

Episodic CAMN: Contextual Attention-Based Memory Networks With Iterative Feedback for Scene Labeling

no code implementations CVPR 2017 Abrar H. Abdulnabi, Bing Shuai, Stefan Winkler, Gang Wang

Scene labeling can be seen as a sequence-sequence prediction task (pixels-labels), and it is quite important to leverage relevant context to enhance the performance of pixel classification.

General Classification Scene Labeling

Reinforcement Learning for Learning Rate Control

no code implementations31 May 2017 Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu

Stochastic gradient descent (SGD), which updates the model parameters by adding a local gradient times a learning rate at each step, is widely used in model training of machine learning algorithms such as neural networks.

reinforcement-learning Reinforcement Learning (RL)

Solving Almost all Systems of Random Quadratic Equations

no code implementations29 May 2017 Gang Wang, Georgios B. Giannakis, Yousef Saad, Jie Chen

This paper deals with finding an $n$-dimensional solution $x$ to a system of quadratic equations of the form $y_i=|\langle{a}_i, x\rangle|^2$ for $1\le i \le m$, which is also known as phase retrieval and is NP-hard in general.


Towards Monetary Incentives in Social Q&A Services

no code implementations3 Mar 2017 Steve T. K. Jan, Chun Wang, Qing Zhang, Gang Wang

Community-based question answering (CQA) services are facing key challenges to motivate domain experts to provide timely answers.

Question Answering

Randomized Block Frank-Wolfe for Convergent Large-Scale Learning

no code implementations27 Dec 2016 Liang Zhang, Gang Wang, Daniel Romero, Georgios B. Giannakis

To circumvent the limitations of existing methods, the present work develops step sizes for RB-FW that enable a flexible selection of the number of blocks to update per iteration while ensuring convergence and feasibility of the iterates.

Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow

no code implementations NeurIPS 2016 Gang Wang, Georgios Giannakis

This paper puts forth a novel algorithm, termed \emph{truncated generalized gradient flow} (TGGF), to solve for $\bm{x}\in\mathbb{R}^n/\mathbb{C}^n$ a system of $m$ quadratic equations $y_i=|\langle\bm{a}_i,\bm{x}\rangle|^2$, $i=1, 2,\ldots, m$, which even for $\left\{\bm{a}_i\in\mathbb{R}^n/\mathbb{C}^n\right\}_{i=1}^m$ random is known to be \emph{NP-hard} in general.

Improving Fully Convolution Network for Semantic Segmentation

no code implementations28 Nov 2016 Bing Shuai, Ting Liu, Gang Wang

In addition, dense skip connections are added so that the context network can be effectively optimized.

Scene Parsing Semantic Segmentation

Sparse Phase Retrieval via Truncated Amplitude Flow

1 code implementation23 Nov 2016 Gang Wang, Liang Zhang, Georgios B. Giannakis, Mehmet Akcakaya, Jie Chen

Upon formulating sparse PR as an amplitude-based nonconvex optimization task, SPARTA works iteratively in two stages: In stage one, the support of the underlying sparse signal is recovered using an analytically well-justified rule, and subsequently, a sparse orthogonality-promoting initialization is obtained via power iterations restricted on the support; and, in the second stage, the initialization is successively refined by means of hard thresholding based gradient-type iterations.

Information Theory Information Theory Optimization and Control

DelugeNets: Deep Networks with Efficient and Flexible Cross-layer Information Inflows

1 code implementation17 Nov 2016 Jason Kuen, Xiangfei Kong, Gang Wang, Yap-Peng Tan

Deluge Networks (DelugeNets) are deep neural networks which efficiently facilitate massive cross-layer information inflows from preceding layers to succeeding layers.

General Classification

Solving Large-scale Systems of Random Quadratic Equations via Stochastic Truncated Amplitude Flow

no code implementations29 Oct 2016 Gang Wang, Georgios B. Giannakis, Jie Chen

A novel approach termed \emph{stochastic truncated amplitude flow} (STAF) is developed to reconstruct an unknown $n$-dimensional real-/complex-valued signal $\bm{x}$ from $m$ `phaseless' quadratic equations of the form $\psi_i=|\langle\bm{a}_i,\bm{x}\rangle|$.


Decision Making Based on Cohort Scores for Speaker Verification

no code implementations27 Sep 2016 Lantian Li, Renyu Wang, Gang Wang, Caixia Wang, Thomas Fang Zheng

In this paper, we propose a decision making approach based on multiple scores derived from a set of cohort GMMs (cohort scores).

Decision Making Speaker Verification

A Siamese Long Short-Term Memory Architecture for Human Re-Identification

no code implementations European Conference on Computer Vision 2016 Rahul Rama Varior, Bing Shuai, Jiwen Lu, Dong Xu, Gang Wang

Matching pedestrians across multiple camera views known as human re-identification (re-identification) is a challenging problem in visual surveillance.

Person Re-Identification

Gated Siamese Convolutional Neural Network Architecture for Human Re-Identification

no code implementations28 Jul 2016 Rahul Rama Varior, Mrinal Haloi, Gang Wang

However, current networks extract fixed representations for each image regardless of other images which are paired with it and the comparison with other images is done only at the final level.

Person Re-Identification

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

no code implementations24 Jul 2016 Jun Liu, Amir Shahroudy, Dong Xu, Gang Wang

To handle the noise and occlusion in 3D skeleton data, we introduce new gating mechanism within LSTM to learn the reliability of the sequential input data and accordingly adjust its effect on updating the long-term context information stored in the memory cell.

Action Analysis Skeleton Based Action Recognition

Context-Aware Gaussian Fields for Non-Rigid Point Set Registration

no code implementations CVPR 2016 Gang Wang, Zhicheng Wang, Yufei Chen, Qiangqiang Zhou, Weidong Zhao

Point set registration (PSR) is a fundamental problem in computer vision and pattern recognition, and it has been successfully applied to many applications.

Solving Systems of Random Quadratic Equations via Truncated Amplitude Flow

no code implementations26 May 2016 Gang Wang, Georgios B. Giannakis, Yonina C. Eldar

This paper presents a new algorithm, termed \emph{truncated amplitude flow} (TAF), to recover an unknown vector $\bm{x}$ from a system of quadratic equations of the form $y_i=|\langle\bm{a}_i,\bm{x}\rangle|^2$, where $\bm{a}_i$'s are given random measurement vectors.

Joint Learning of Siamese CNNs and Temporally Constrained Metrics for Tracklet Association

no code implementations15 May 2016 Bing Wang, Li Wang, Bing Shuai, Zhen Zuo, Ting Liu, Kap Luk Chan, Gang Wang

Then the Siamese CNN and temporally constrained metrics are jointly learned online to construct the appearance-based tracklet affinity models.

Multi-Object Tracking Multi-Task Learning

Recurrent Attentional Networks for Saliency Detection

no code implementations CVPR 2016 Jason Kuen, Zhenhua Wang, Gang Wang

Convolutional-deconvolution networks can be adopted to perform end-to-end saliency detection.

Saliency Detection

NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis

1 code implementation CVPR 2016 Amir Shahroudy, Jun Liu, Tian-Tsong Ng, Gang Wang

Recent approaches in depth-based human activity analysis achieved outstanding performance and proved the effectiveness of 3D representation for classification of action classes.

Action Classification General Classification +1

Multi-task CNN Model for Attribute Prediction

no code implementations4 Jan 2016 Abrar H. Abdulnabi, Gang Wang, Jiwen Lu, Kui Jia

Each CNN will generate attribute-specific feature representations, and then we apply multi-task learning on the features to predict their attributes.

Multi-Task Learning

Recent Advances in Convolutional Neural Networks

no code implementations22 Dec 2015 Jiuxiang Gu, Zhenhua Wang, Jason Kuen, Lianyang Ma, Amir Shahroudy, Bing Shuai, Ting Liu, Xingxing Wang, Li Wang, Gang Wang, Jianfei Cai, Tsuhan Chen

In the last few years, deep learning has led to very good performance on a variety of problems, such as visual recognition, speech recognition and natural language processing.

speech-recognition Speech Recognition

Hierarchical Invariant Feature Learning with Marginalization for Person Re-Identification

no code implementations30 Nov 2015 Rahul Rama Varior, Gang Wang

This paper addresses the problem of matching pedestrians across multiple camera views, known as person re-identification.

Metric Learning Person Re-Identification

Video Tracking Using Learned Hierarchical Features

no code implementations25 Nov 2015 Li Wang, Ting Liu, Gang Wang, Kap Luk Chan, Qingxiong Yang

The adaptation is conducted in both layers of the deep feature learning module so as to include appearance information of the specific target object.

Domain Adaptation Network Embedding +1

Tracklet Association by Online Target-Specific Metric Learning and Coherent Dynamics Estimation

no code implementations20 Nov 2015 Bing Wang, Gang Wang, Kap Luk Chan, Li Wang

In this paper, we present a novel method based on online target-specific metric learning and coherent dynamics estimation for tracklet (track fragment) association by network flow optimization in long-term multi-person tracking.

Metric Learning

Towards Predicting the Likeability of Fashion Images

no code implementations17 Nov 2015 Jinghua Wang, Abrar Abdul Nabi, Gang Wang, Chengde Wan, Tian-Tsong Ng

Given attributes as representations, we propose to learn a ranking SPN (sum product networks) to rank pairs of fashion images.

Learning Fine-grained Features via a CNN Tree for Large-scale Classification

no code implementations14 Nov 2015 Zhenhua Wang, Xingxing Wang, Gang Wang

The key idea is to build a tree structure that could progressively learn fine-grained features to distinguish a subset of classes, by learning features only among these classes.

General Classification Image Classification

Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks

no code implementations13 Sep 2015 Zhen Zuo, Bing Shuai, Gang Wang, Xiao Liu, Xingxing Wang, Bing Wang

In this manuscript, we integrate CNNs with HRNNs, and develop end-to-end convolutional hierarchical recurrent neural networks (C-HRNNs).

General Classification Image Classification

DAG-Recurrent Neural Networks For Scene Labeling

no code implementations CVPR 2016 Bing Shuai, Zhen Zuo, Gang Wang, Bing Wang

In image labeling, local representations for image units are usually generated from their surrounding image patches, thus long-range contextual information is not effectively encoded.

General Classification Scene Labeling +1

Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification

no code implementations21 Aug 2015 Zhen Zuo, Gang Wang, Bing Shuai, Lifan Zhao, Qingxiong Yang

In order to encode the class correlation and class specific information in image representation, we propose a new local feature learning approach named Deep Discriminative and Shareable Feature Learning (DDSFL).

General Classification Image Classification

Multimodal Multipart Learning for Action Recognition in Depth Videos

no code implementations31 Jul 2015 Amir Shahroudy, Gang Wang, Tian-Tsong Ng, Qingxiong Yang

We propose a joint sparse regression based learning method which utilizes the structured sparsity to model each action as a combination of multimodal features from a sparse set of body parts.

Action Recognition feature selection +2

Integrating Parametric and Non-Parametric Models For Scene Labeling

no code implementations CVPR 2015 Bing Shuai, Gang Wang, Zhen Zuo, Bing Wang, Lifan Zhao

We adopt Convolutional Neural Networks (CNN) as our parametric model to learn discriminative features and classifiers for local patch classification.

General Classification Metric Learning +1

Deep Hashing for Compact Binary Codes Learning

no code implementations CVPR 2015 Venice Erin Liong, Jiwen Lu, Gang Wang, Pierre Moulin, Jie zhou

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for large scale visual search.

Multi-Manifold Deep Metric Learning for Image Set Classification

no code implementations CVPR 2015 Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin, Jie zhou

In this paper, we propose a multi-manifold deep metric learning (MMDML) method for image set classification, which aims to recognize an object of interest from a set of image instances captured from varying viewpoints or under varying illuminations.

Classification General Classification +1

Learning Invariant Color Features for Person Re-Identification

no code implementations4 Oct 2014 Rahul Rama Varior, Gang Wang, Jiwen Lu

We model color feature generation as a learning problem by jointly learning a linear transformation and a dictionary to encode pixel values.

Person Re-Identification

Tracklet Association with Online Target-Specific Metric Learning

no code implementations CVPR 2014 Bing Wang, Gang Wang, Kap Luk Chan, Li Wang

In our method, target-specific similarity metrics are learned, which give rise to the appearance-based models used in the tracklet affinity estimation.

Metric Learning

DL-SFA: Deeply-Learned Slow Feature Analysis for Action Recognition

no code implementations CVPR 2014 Lin Sun, Kui Jia, Tsung-Han Chan, Yuqiang Fang, Gang Wang, Shuicheng Yan

In this paper, we propose to combine SFA with deep learning techniques to learn hierarchical representations from the video data itself.

Action Recognition Temporal Action Localization

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